Hydrometeor Classification of Winter Precipitation in Northern China Based on Multi-Platform Radar Observation System

Abstract

Hydrometeor classification remains a challenge in winter precipitation cloud systems. To address this issue, 42 snowfall events were investigated based on a multi-platform radar observation system (i.e., X-band dual-polarization radar, Ka-band millimeter wave cloud radar, microwave radiometer, airborne equipment, etc.) in the mountainous region of northern China from 2016 to 2020. A fuzzy logic classification method is proposed to identify the particle phases, and the retrieval result was further verified with ground-based radar observation. Moreover, the hydrometeor characteristics were compared with the numerical simulations to clarify the reliability of the proposed hydrometeor classification approach. The results demonstrate that the X-/Ka- band radars are capable of identifying hydrometeor phases in winter precipitation in accordance with both ground observations and numerical simulations. Three particle categories, including snow, graupel and the mixture of snow and graupel are also detected in the winter precipitation cloud system, and there are three vertical layers identified from top to bottom, including the ice crystal layer, snow-graupel mixed layer and snowflake layer. Overall, this study has the potential for improving the understanding of microphysical processes such as freezing, deposition and aggregation of ice crystal particles in the winter precipitation cloud system.

Multiple Characteristics of Precipitation Inferred from Wind Profiler Radar Doppler Spectra

“…Wind components were computed with the Aerologie Laboratory Wind Profiler Processing (ALWPP) [28] (Method1), and compared with the new proposed methodology named University of Barcelona Wind Profiler Processing (UBWPP), hereafter Method2. (25) These equations were derived and used in [28] to estimate rainfall kinetic energy with radar data, complementing previous studies of soil erosion effects of rainfall made with disdrometric measurements [44].…”

Dual-Polarization Radar Fingerprints of Precipitation Physics: A Review

“…For example, there is a rich literature of studies developing and applying hydrometeor classification algorithms (HCAs), also referred to as hydrometeor identification or particle identification algorithms, which categorize individual pixels in graphical displays of radar data by the inferred dominant backscattering hydrometeor type. Such HCAs have been implemented using a variety of techniques, including theoretically or empirically determined thresholds for the different polarimetric radar variables that correspond to various hydrometeor types (e.g., [8][9][10]), fuzzy logic or neuro-fuzzy logic approaches (e.g., [1,[11][12][13][14][15][16][17][18][19][20][21], among many others), and more data-driven approaches such as hierarchical clustering or support vector machines (e.g., [22][23][24][25][26], among many others). There is a good review of these approaches in [27].…”